The goals of the Belgian Neuromuscular Diseases Registry (BNMDR) are: to enable epidemiological research aimed at evaluating the importance of neuromuscular diseases and patient characteristics, to promote health services for patients with a neuromuscular disease, to provide information to public health authorities for planning of health care in Belgium, and to improve patient recruitment for clinical trials.
Patients’ enrollment increases every year since the registry’s creation in 2008. In 2017, a total number of 5,765 patients were registered, resulting in a Belgian prevalence estimate of 50.8 neuromuscular patients per 100,000 population. Patients’ recruitment was better in the north than in the south of the country. This is presumably due to the geographical distribution of the reference centers collecting the data. Although the gap between those two regions tends to decrease year after year, an under-registration of patients coming from the southwest remains evident. This continuous observation highlights the need of the recognition of an expert center in this area.
The particularity of a general registry dedicated to neuromuscular diseases (compared to other health care registries) is that the patient population is diverse. Neuromuscular diseases indeed comprise various rare disorders affecting the anterior horn cells, peripheral nerves, muscles or neuromuscular junctions. Some disorders are genetic, while others are not. The vast majority of them are degenerative, sometimes with a fatal outcome in the short or long term. Some occur during childhood, and others occur during adulthood. In consequence, patients constitute a heterogeneous group making the extraction of global trends difficult.
For 2017, General demographic data showed a slightly higher number of males than females with a neuromuscular disease (N = 3,145 versus N = 2,620 respectively). The age range varied between 2 months and 97 years, with a median of 48 years (pc25 = 27 years and pc75 = 62 years). The vast majority of registered patients (75.3%) were ambulant, a significant proportion (19.7%) were wheelchair-bound and life support was needed in 2.0%. Diagnosis was considered final (with or without genetic confirmation) in about three quarters of patients (74.6%). Further, 220 deaths were reported, of which 135 (61.4%) occurred in patients suffering from Amyotrophic Lateral Sclerosis (ALS).
The ten most prevalent diseases of 2017 were, in order of significance: Hereditary Motor and Sensory Neuropathy, Myotonic Dystrophy type 1, ALS, Hereditary Spastic Paraplegia, Duchenne Muscular Dystrophy (DMD), Chronic Inflammatory Demyelinating Polyneuropathy, Facioscapulohumeral Dystrophy, Limb Girdle Muscular Dystrophy, Spinocerebellar Ataxias, and Postpolio Syndrome. Those ten diseases, accounting for 63.2% of all registrations, are analyzed in detail in the present report. It should be noted that this hierarchy is based on the NIHDI classification in which the four sub-types of Spinal Muscular Atrophy (SMA) are divided in four distinct disease groups. When pooled together, SMA was ranked 9th in the list.
For two defined groups of diseases, i.e. DMD/Becker Muscular Dystrophy (BMD) and SMA, the registry also collects additional data within the international TREAT-NMD network (Translational Research in Europe – Assessment and Treatment of NeuroMuscular Diseases). Those specific data are also analyzed in the present report. TREAT-NMD aims to advance diagnosis, care and treatment for neuromuscular patients. A total of 302 DMD patients, 109 BMD patients and 212 SMA patients were registered in 2017, making them eligible for feasibility studies and recruitment enquiries.
To optimize the quality of care in the reference centers, each center received a feedback report with benchmarking information. In addition, the quality of the 2017 data entry was subjected to a 5% verification of the files encoded within each reference center. The average percentage of mistakes was 12.7%, with a minimum of 0% and a maximum of 33.3%. It should be mentioned that the number of verified files was rather low in some centers, resulting in a artificially high error percentage. In the future, we will rethink our methodology to avoid such bias.
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